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Mathematical models and information systems in humanitarian supply chain management
Muhammad Salman Habib,Young Hae Lee,Saad Memon 대한산업공학회 2015 대한산업공학회 추계학술대회논문집 Vol.2015 No.11
In the past decade humanitarian supply chain (HSC) has attracted attention of researchers due to increasing frequency of disasters. The factor of unpredictability and complexity in the occurrence of disasters, demands some better measures in order to reduce losses both human and economic. Viewing this need the field of HSC has been served with diverse nature of mathematical techniques and information systems that has played important role to overcome problems encountered in the planning of different phases of disaster. Mathematical models enable us to exploit limited resources in an efficient manner while information systems enable us to make timely decisions by providing access to real time information. This variety of research work in the field of HSC is motivating the need of a systematic literature. So, viewing the need this paper presents the review of the mathematical contributions made in last decade and information systems being used in HSC. A systematic literature review methodology has been used for this paper. There are goals to write this paper. First, to conduct an up-to-date survey of mathematical models and information systems being utilized in HSC and the second one to highlight the potential research areas which require attention of researchers.
Alumina joining using magnesium- or calcium-aluminosilicate glass-ceramic filler comprising Si3N4
SALMAN MUHAMMAD,Ryu Sung-Soo,윤당혁 한국세라믹학회 2023 한국세라믹학회지 Vol.60 No.3
Magnesium- and calcium-aluminosilicate (MAS and CAS, respectively) glass-ceramics containing different amounts of Si3N4 (0, 20, 40, and 60 wt.%) were examined as fillers for alumina joining. After applying filler paste onto the alumina base plate via screen-printing, joining was performed at 1500 °C for 1 h at 12 MPa pressure in a N 2 atmosphere. The phase and microstructural evolution in the joint interlayer and the resulting joint strength were analyzed as a function of the Si 3N4 content. Both MAS and CAS fillers with up to 40 wt.% Si 3N4 wetted the alumina surface after melting, while those with 60 wt.% Si 3N4 exhibited incomplete melting. The variation in joint strength was explained by the evolution of phases at the interface and the thermal expansion coeffi cient mismatch between the filler and alumina base plate. The highest joint strength of 317 ± 39 MPa was obtained for the MAS fi ller with 40 wt.% Si 3N4.
Dynamics Analysis and Control of 5 DOF Robot Manipulator
Muhammad Salman,Hamza Khan,Saad Jamshed Abbasi,Min Cheol Lee 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
The accurate dynamic model of the robot manipulator is essential for better control performance. Dynamic modelling refers to deriving such equations that explicitly describe the relationship between force and motion in a system. There are several methods to solve for the dynamics of the system. The main concern while doing dynamics is to check its reliability and verification. In this paper, Lagrange Euler (L-E) method is used to dynamically model a five-degrees-of-freedom (DOF) robot manipulator and verified through 3D model of robot in Simulink, simscape multibody toolbox. Followed by the implementation of a proportional-integral-derivative (PID) control with a low pass filter ‘N’ (PIDN) on the derived system. The low pass filter enhances the control performance by eliminating the effect of derivative term’s fluctuations (noise). Furthermore, Ziegler Nichols"s closed-loop tuning method is used to optimally tune the PID control. The derived model and control algorithm simulations have been performed in MATLAB. The simulations results illustrated that the derived model is controllable which indicates the correctness of the derived model.
Pest Prediction in Rice using IoT and Feed Forward Neural Network
( Muhammad Salman Latif ),( Rafaqat Kazmi ),( Nadia Khan ),( Rizwan Majeed ),( Sunnia Ikram ),( Malik Muhammad Ali-shahid ) 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.1
Rice is a fundamental staple food commodity all around the world. Globally, it is grown over 167 million hectares and occupies almost 1/5<sup>th</sup> of total cultivated land under cereals. With a total production of 782 million metric tons in 2018. In Pakistan, it is the 2<sup>nd</sup> largest crop being produced and 3<sup>rd</sup> largest food commodity after sugarcane and rice. The stem borers a type of pest in rice and other crops, Scirpophaga incertulas or the yellow stem borer is very serious pest and a major cause of yield loss, more than 90% damage is recorded in Pakistan on rice crop. Yellow stem borer population of rice could be stimulated with various environmental factors which includes relative humidity, light, and environmental temperature. Focus of this study is to find the environmental factors changes i.e., temperature, relative humidity and rainfall that can lead to cause outbreaks of yellow stem borers. this study helps to find out the hot spots of insect pest in rice field with a control of farmer’s palm. Proposed system uses temperature, relative humidity, and rain sensor along with artificial neural network to predict yellow stem borer attack and generate warning to take necessary precautions. result shows 85.6% accuracy and accuracy gradually increased after repeating several training rounds. This system can be good IoT based solution for pest attack prediction which is cost effective and accurate.